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Disproportionality analysis of adverse events associated with degarelix: a real-world study from the FDA Adverse Event Reporting System (FAERS) database.
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Lin Xiaojuan, Guo Liwei, Lin Yansheng, Zheng Huishan, Huang Xiaohong, Wang Jing
Аннотация
PURPOSE: This study aimed to detect adverse event (AE) signals associated with degarelix by analyzing data from the US FDA Adverse Event Reporting System (FAERS), so as to provide evidence for its safe clinical use.
METHODS: Data from the FAERS database spanning January 2014 to December 2024 were extracted, cleaned, and deduplicated. A disproportionality analysis was performed to identify significant AE signals by calculating and comparing four established metrics: the Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), the Information Component of the Bayesian Confidence Propagation Neural Network (BCPNN), and the Empirical Bayes Geometric Mean (EBGM). Statistical significance for signal detection was defined as exceeding the predefined thresholds for each respective metric. AEs were coded with the Medical Dictionary for Regulatory Activities (MedDRA).
RESULTS: Among 17,048,812 AE reports recorded in FAERS during the study period, 2,984 were associated with degarelix. These reports spanned 22 System Organ Classes (SOC), and 130 Preferred Terms (PTs) showed significant disproportionate reporting based on the four algorithms. Injection site reactions and hot flush were consistent with common AEs listed in the label. It is noteworthy that 53 AEs, such as interstitial lung disease, cardiac failure, osteoporotic fracture, and hyperkalaemia, were absent from the label and may represent previously unreported risks that warrant further study.
CONCLUSION: Our findings not only validate the established safety data for degarelix but also reveal potential new risks, necessitating continued post-marketing vigilance to guide its safer clinical application.
METHODS: Data from the FAERS database spanning January 2014 to December 2024 were extracted, cleaned, and deduplicated. A disproportionality analysis was performed to identify significant AE signals by calculating and comparing four established metrics: the Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), the Information Component of the Bayesian Confidence Propagation Neural Network (BCPNN), and the Empirical Bayes Geometric Mean (EBGM). Statistical significance for signal detection was defined as exceeding the predefined thresholds for each respective metric. AEs were coded with the Medical Dictionary for Regulatory Activities (MedDRA).
RESULTS: Among 17,048,812 AE reports recorded in FAERS during the study period, 2,984 were associated with degarelix. These reports spanned 22 System Organ Classes (SOC), and 130 Preferred Terms (PTs) showed significant disproportionate reporting based on the four algorithms. Injection site reactions and hot flush were consistent with common AEs listed in the label. It is noteworthy that 53 AEs, such as interstitial lung disease, cardiac failure, osteoporotic fracture, and hyperkalaemia, were absent from the label and may represent previously unreported risks that warrant further study.
CONCLUSION: Our findings not only validate the established safety data for degarelix but also reveal potential new risks, necessitating continued post-marketing vigilance to guide its safer clinical application.